The definition of the data mining can be told as to extract information or knowledge from large volumes of data. One of the main challenging area of data mining is classification. There are so many different classification algorithm in... more
The definition of the data mining can be told as to extract information or knowledge from large volumes of data. One of the main challenging area of data mining is classification. There are so many different classification algorithm in literature ranging from statistical based to artificial intelligence based. This study make use of Waikato Environment for Knowledge Analysis or in short, WEKA to compare the different classification techniques on different medical datasets. 23 different classification techniques were applied to three different medical datasets namely EEG Eye State, Fertility and Thoracic Surgery Medical Datasets that were taken from UCI Machine Learning Repository. The results showed that Multilayer Perceptron (MLP) had highest accuracy for Fertility Dataset (90%), three different techniques namely Bagging, Dagging and Grading had highest and same accuracies for Thoracic Surgery Data Set (85.1064%) and finally Kstar had highest accuracy for EEG Eye State Dataset (96.7757%).
Real estate market is very effective in today's world but finding best price for house is a big problem. This problem creates a propose of this work. In this study, we try to compare and find best prediction algorithms on disorganized... more
Real estate market is very effective in today's world but finding best price for house is a big problem. This problem creates a propose of this work. In this study, we try to compare and find best prediction algorithms on disorganized house data. Dataset was collected from real estate websites and three different regions selected for this experiment. KNN, KSTAR, Simple Linear Regression, Linear Regression, RBFNetwork and Decision Stump algorithms were used. This study shows us KStar and KNN algorithms are better than the other prediction algorithms for disorganized data.